Method and system for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding seam

Abstract

The invention belongs to the technical field of laser welding defect prediction, and discloses an aluminum alloy laser welding seam three-dimensional solidification crack sensitivity prediction method, which comprises the following steps: accurately calculating a lap joint temperature / solid fraction (TB / fB) and a T-fS curve of adjacent dendrites of a polycrystalline structure in a welding seam pasty area through laser welding macro-micro thermal mass coupling simulation; a novel solidification crack sensitivity prediction method fusing microstructure information is provided, accurate prediction of the solidification crack sensitivity of aluminum alloy laser welding is achieved, the solidification crack inhibition mechanism that an ultra-fine equiaxed crystal structure shortens an intergranular liquid phase channel and reduces solute segregation is disclosed, and the stability of the solidification crack sensitivity is improved. The method has very important engineering application significance for realizing solidification crack-free welding of the high-strength aluminum alloy thick-wall component.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser welding defect prediction, and in particular relates to a method and system for predicting three-dimensional solidification crack sensitivity of an aluminum alloy laser welding weld. Background Art

[0002] Solidification cracks are one of the common defects in aluminum alloy welding. Solidification cracks in aluminum alloy welding usually occur in the mushy zone of the molten pool (i.e., the liquid-solid coexistence zone), which is closely related to the evolution behavior of the dendrite structure during the solidification process. When the dendrite grows in the molten pool, the low-melting-point eutectic phase segregates between the dendrites and produces a liquid film or droplets on the dendrites, forming a dendrite network structure in the mushy zone (low ductility); at the same time, due to factors such as solidification shrinkage and thermal shrinkage of the parent material, the mushy zone will produce a large shrinkage deformation; when the shrinkage deformation exceeds the ductility of the dendrite network structure and the liquid phase reflux shrinkage compensation capacity is insufficient, solidification cracks will occur. Related studies have shown that the low-ductility dendrite network structure in the mushy zone, such as liquid film morphology, grain morphology and size, directly affects the solidification crack sensitivity. To this end, it is of great significance to clarify the evolution law of the solidification structure of aluminum alloy welding, reveal the changes in the dendrite network structure in the late solidification period, and realize the prediction of solidification crack sensitivity to inhibit solidification cracks.

[0003] At present, the prediction methods for several welding solidification cracks of aluminum alloys are mainly as follows: 202310956914.4, this patent uses a macro-micro coupling method to obtain the information of organizational evolution in the two-dimensional solidification process, uses the RDG model to calculate the pressure drop, and compares the calculated pressure drop result with the liquid film bearing capacity model to determine the occurrence of hot cracks. 202410092277.5, this patent proposes a method for deriving a criterion for directional solidification hot crack sensitivity under a unified permeability, and the permeability values ​​of different regions are calculated simultaneously with high precision. 201710779447.7 Through experiments, based on the Clyne-Davies model, a new method for predicting the hot crack tendency of alloys is proposed. However, there are several problems that need to be solved: First, the prediction is mainly carried out in two dimensions, and the prediction of the three-dimensional solidification crack sensitivity of the weld is still to be carried out; second, the key overlap temperature (TB) and T-fS curve in the prediction of solidification crack sensitivity are still mainly estimated or tested, and the prediction accuracy is low.

[0004] Through the above analysis, the problems and defects of the prior art are as follows:

[0005] (1) The prediction is mainly based on two dimensions, and the prediction of three-dimensional solidification crack sensitivity of welds is still to be carried out.

[0006] (2) The key lap temperature (TB) and T-fS curve in the prediction of solidification crack sensitivity are still mainly estimated or tested, and the prediction accuracy is low. Summary of the invention

[0007] In view of the problems existing in the prior art, the present invention provides a method for predicting the three-dimensional solidification crack sensitivity of an aluminum alloy laser welding weld.

[0008] The present invention is implemented as follows: a method for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds comprises:

[0009] Step 1, obtaining macroscopic temperature field information;

[0010] A macroscopic heat and mass transfer model of laser welding is established based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations.

[0011] Step 2: Microstructure simulation of the mushy area and acquisition of key information;

[0012] The temperature field data obtained from the macroscopic simulation is used as input to perform isothermal three-dimensional mushy zone microstructure simulation considering the grain boundaries of adjacent grains.

[0013] Step 3, solidification crack sensitivity prediction;

[0014] Based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension.

[0015] Furthermore, the macroscopic temperature field information is obtained:

[0016] A macroscopic heat and mass transfer model of laser welding is established based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations. Three-dimensional geometric modeling is carried out based on the actual welding specimen, the model is meshed, and the thermophysical property parameters, initial conditions, and boundary condition information are set to calculate the macroscopic heat flow of aluminum alloy laser welding under thermal-mass-force coupling. The depth of penetration and width of the simulation results are observed, and the temperature field data of the entire weld at different times are extracted when the depth of penetration and width of the weld are basically stable.

[0017] Furthermore, the microstructure simulation and key information acquisition of the mushy zone:

[0018] The temperature field data obtained from the macroscopic simulation is used as input, and the isothermal three-dimensional mushy zone microstructure simulation is performed considering the grain boundaries of adjacent grains. The numerical simulation results are visualized. When two adjacent grains overlap, the judgment condition is that the liquid phase fraction at the boundary of adjacent grains is less than 0.5. At this time, the temperature of the entire calculation domain is taken as the overlap point temperature TB, and the solid phase fraction of the calculation domain is taken as the overlap point solid phase fraction fB. The temperature-solid phase fraction curve T-fS curve in the entire calculation domain is extracted.

[0019] Furthermore, the calculation dimension includes two-dimensional / three-dimensional.

[0020] Furthermore, the solidification crack sensitivity prediction is:

[0021] Based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension:

[0022] (1) For a two-dimensional columnar crystal, draw a T-|dT / d(fs)| curve. When f=fB, SCS=|dT / d(fs)|;

[0023] (2) For a two-dimensional equiaxed crystal, draw the T-|dT / d(fs)1 / 2| curve. When f=fB, SCS=|dT / d(fs)1 / 2|;

[0024] (3) For three-dimensional columnar crystals, draw the T-|dT / d(fs)1 / 2| curve. When f=fB, SCS=|dT / d(fs)1 / 2|;

[0025] (4) For three-dimensional equiaxed crystals, draw the T-|dT / d(fs)1 / 3| curve. When f=fB, SCS=|dT / d(fs)1 / 3|.

[0026] Another object of the present invention is to provide a three-dimensional solidification crack sensitivity prediction system for aluminum alloy laser welding welds, comprising:

[0027] Macro temperature field information acquisition module, used to obtain macro temperature field information; based on flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, a macro heat and mass transfer model for laser welding is established;

[0028] Key information acquisition module, used for mushy zone microstructure simulation and key information acquisition; the temperature field data obtained from the macroscopic simulation is used as input, and the isothermal three-dimensional mushy zone microstructure simulation is performed considering the grain boundaries of adjacent grains;

[0029] The prediction module is used to predict solidification crack sensitivity; based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension.

[0030] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for predicting the three-dimensional solidification crack sensitivity of the aluminum alloy laser welding weld.

[0031] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the steps of the method for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds.

[0032] Another object of the present invention is to provide an information data processing terminal, which is used to implement the three-dimensional solidification crack sensitivity prediction system of the aluminum alloy laser welding weld.

[0033] In combination with the above technical solutions and the technical problems solved, please analyze the advantages and positive effects of the technical solutions to be protected by the present invention from the following aspects:

[0034] First, the present invention provides a method for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds. This method has successfully achieved the prediction of the three-dimensional solidification crack sensitivity of high-strength aluminum alloys, and based on this, achieved the suppression of solidification cracks in aluminum alloy laser welding.

[0035] (1) The present invention uses macro-micro thermal-mass coupling simulation of laser welding to accurately calculate the overlap point temperature / solid fraction (TB / fB) and T-fS curve of adjacent dendrites in the polycrystalline structure of the mushy zone of the weld;

[0036] (2) A new method for predicting solidification crack sensitivity by integrating microstructural information was proposed, which achieved accurate prediction of solidification crack sensitivity during laser welding of aluminum alloys and revealed the solidification crack inhibition mechanism of ultrafine equiaxed crystal structure, which shortened the intergranular liquid phase channel and reduced solute segregation. This has very important engineering application significance for achieving solidification crack-free welding of high-strength aluminum alloy thick-walled components.

[0037] Second, the technical solution of the present invention fills the technical gap in the industry at home and abroad: the existing welding solidification crack prediction methods at home and abroad are mainly based on two dimensions, and studies have shown that there is a large deviation between the two-dimensional prediction results and the actual results. The present invention provides an aluminum alloy solidification crack prediction model to fill the gap in the three-dimensional model for aluminum alloy solidification crack prediction at home and abroad. At the same time, the present invention introduces the macroscopic temperature field into the solidification crack prediction, uses macroscopic information to make up for the deviation of the microscopic prediction results and improves the prediction accuracy, making up for the problem of low accuracy in the prediction of aluminum alloy welding solidification cracks at home and abroad.

[0038] The technical solution of the present invention solves a technical problem that people have been eager to solve but have never been able to solve: the key parameters in the prediction of aluminum alloy welding solidification cracks have always been based on estimation or experimental evaluation, and the prediction accuracy is low. The present invention proposes a solidification crack sensitivity prediction method that combines the macroscopic temperature field with the microstructural information to solve the problem of low prediction accuracy. At the same time, a three-dimensional solidification crack prediction model is innovatively constructed, breaking through the problem of low prediction accuracy of the two-dimensional model that people have always had.

[0039] Whether the technical solution of the present invention overcomes technical prejudice: Due to the long calculation time and high cost of numerical simulation, it has been limited in the process of practical application. However, the study of solidification cracks cannot be separated from numerical simulation. Therefore, people generally use two-dimensional low-precision prediction methods to reduce calculation time and cost. The present invention adopts MPI parallel computing technology, which greatly improves the calculation efficiency of the numerical model, breaks through the dilemma that the prediction accuracy and cost of solidification cracks cannot be achieved at the same time, and makes efficient and high-precision prediction of aluminum alloy solidification cracks possible.

[0040] Third, the technical solution of the present invention effectively solves the technical problems of low prediction accuracy of three-dimensional solidification crack sensitivity of welds in existing aluminum alloy laser welding, long debugging time, and difficulty in real-time adjustment in industrial applications. Traditional methods usually rely on a single temperature field or only predict crack sensitivity based on static microstructure characteristics, resulting in inaccurate prediction results and difficulty in dealing with variable parameters in complex welding processes. In particular, traditional solutions lack targeted data processing and feedback mechanisms, and cannot effectively deal with the impact of parameter fluctuations during welding, thereby limiting the optimization and stability of the welding process.

[0041] The present invention significantly improves the prediction accuracy of weld solidification crack sensitivity through the collaborative work of multiple modules. The temperature field acquisition module combines flow and heat transfer control, ray tracing, driving force and thermal boundary control equations to establish a dynamic temperature field model to reflect the heat conduction and heat distribution during the welding process in real time. This module not only obtains more accurate temperature field data, but also, with the support of the dynamic feedback adjustment unit, can dynamically adjust according to the real-time monitored welding parameters to ensure that the temperature field data is consistent with the actual welding process, significantly improving the real-time and accuracy of the prediction.

[0042] In addition, the present invention introduces a grain growth direction prediction unit in the microstructure simulation, which makes the simulation of grain overlap and morphological evolution more accurate and further refines the microstructure of the weld. This module can effectively capture the grain growth in the three-dimensional mushy zone, and provides important data such as grain boundary energy and solid phase fraction, providing a solid data foundation for subsequent crack sensitivity prediction. The crack sensitivity prediction module realizes the dynamic calculation and hierarchical management of SCS (solidification crack sensitivity value) through the data comparison and verification unit, making the crack sensitivity prediction more accurate and comprehensive. In addition, the visual report generated by the system provides operators with intuitive crack sensitivity levels and risk prompts, which helps to quickly adjust welding parameters.

[0043] In summary, the present invention has made significant technical progress in improving the crack sensitivity prediction accuracy, shortening the debugging time and enhancing the welding stability. It has broad industrial application value and provides reliable technical support for the optimization of aluminum alloy welding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of a method for predicting three-dimensional solidification crack sensitivity of an aluminum alloy laser welding weld provided in an embodiment of the present invention.

[0045] Figure 2 It is a structural block diagram of a three-dimensional solidification crack sensitivity prediction system for aluminum alloy laser welding welds provided in an embodiment of the present invention.

[0046] Figure 3 It is a schematic diagram of macroscopic heat and mass transfer and a control equation diagram of laser welding provided in an embodiment of the present invention.

[0047] Figure 4 It is a macroscopic heat and mass transfer calculation domain diagram provided by an embodiment of the present invention.

[0048] Figure 5 It is a temperature curve diagram of different positions of the weld provided by an embodiment of the present invention.

[0049] Figure 6 It is a schematic diagram of a three-dimensional polycrystalline phase field model and a control equation diagram provided by an embodiment of the present invention.

[0050] Figure 7 It is a three-dimensional equiaxed crystal solidification process and solidification crack sensitivity diagram under different initial nucleation rates provided by an embodiment of the present invention.

[0051] Figure 8 It is a columnar crystal morphology diagram under different initial primary dendrite spacings provided by an embodiment of the present invention.

[0052] Fig. 9 This is a diagram showing the change of the solid-liquid interface morphology of dendritic and non-dendritic columnar crystals with temperature provided by an embodiment of the present invention.

[0053] Fig.10 It is a T-fS curve of dendritic and non-dendritic columnar crystals and a solidification crack sensitivity coefficient diagram provided by an embodiment of the present invention.

[0054] Fig.11 This is a simulation result diagram of the change of solid-liquid interface in the columnar crystal region with temperature when the grain boundary energy is considered, provided by an embodiment of the present invention.

[0055] Fig.12 The embodiment of the present invention provides a liquid phase fraction diagram at the center line of the grain boundary between two adjacent grains at the eutectic temperature. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0057] like Figure 1 As shown, a method for predicting three-dimensional solidification crack sensitivity of an aluminum alloy laser welding weld provided by an embodiment of the present invention comprises the following steps:

[0058] S101, acquisition of macroscopic temperature field information;

[0059] A macroscopic heat and mass transfer model of laser welding is established based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations.

[0060] S102, microstructure simulation and key information acquisition in mushy zone;

[0061] The temperature field data obtained from the macroscopic simulation is used as input to perform isothermal three-dimensional mushy zone microstructure simulation considering the grain boundaries of adjacent grains.

[0062] S103, solidification crack susceptibility prediction;

[0063] Based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension.

[0064] The macroscopic temperature field information acquisition provided by the embodiment of the present invention is as follows:

[0065] A macroscopic heat and mass transfer model of laser welding is established based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations. Three-dimensional geometric modeling is carried out based on the actual welding specimen, the model is meshed, and the thermophysical property parameters, initial conditions, and boundary condition information are set to calculate the macroscopic heat flow of aluminum alloy laser welding under thermal-mass-force coupling. The depth of penetration and width of the simulation results are observed, and the temperature field data of the entire weld at different times are extracted when the depth of penetration and width of the weld are basically stable.

[0066] The microstructure simulation and key information acquisition of the mushy zone provided by the embodiment of the present invention:

[0067] The temperature field data obtained from the macroscopic simulation is used as input, and the isothermal three-dimensional mushy zone microstructure simulation is performed considering the grain boundaries of adjacent grains. The numerical simulation results are visualized. When two adjacent grains overlap, the judgment condition is that the liquid phase fraction at the boundary of adjacent grains is less than 0.5. At this time, the temperature of the entire calculation domain is taken as the overlap point temperature TB, and the solid phase fraction of the calculation domain is taken as the overlap point solid phase fraction fB. The temperature-solid phase fraction curve T-fS curve in the entire calculation domain is extracted.

[0068] The calculation dimensions provided by the embodiment of the present invention include two-dimensional / three-dimensional.

[0069] Solidification crack sensitivity prediction provided by the embodiment of the present invention:

[0070] Based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension:

[0071] (1) For a two-dimensional columnar crystal, draw a T-|dT / d(fs)| curve. When f=fB, SCS=|dT / d(fs)|;

[0072] (2) For a two-dimensional equiaxed crystal, draw the T-|dT / d(fs)1 / 2| curve. When f=fB, SCS=|dT / d(fs)1 / 2|;

[0073] (3) For three-dimensional columnar crystals, draw the T-|dT / d(fs)1 / 2| curve. When f=fB, SCS=|dT / d(fs)1 / 2|;

[0074] (4) For three-dimensional equiaxed crystals, draw the T-|dT / d(fs)1 / 3| curve. When f=fB, SCS=|dT / d(fs)1 / 3|.

[0075] like Figure 2 As shown, a three-dimensional solidification crack sensitivity prediction system for aluminum alloy laser welding weld provided by an embodiment of the present invention includes:

[0076] Macro temperature field information acquisition module, used to obtain macro temperature field information; based on flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, a macro heat and mass transfer model for laser welding is established;

[0077] Key information acquisition module, used for mushy zone microstructure simulation and key information acquisition; the temperature field data obtained from the macroscopic simulation is used as input, and the isothermal three-dimensional mushy zone microstructure simulation is performed considering the grain boundaries of adjacent grains;

[0078] The prediction module is used to predict solidification crack sensitivity; based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension.

[0079] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for predicting the three-dimensional solidification crack sensitivity of the aluminum alloy laser welding weld.

[0080] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the steps of the method for predicting the three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds.

[0081] Another object of the present invention is to provide an information data processing terminal, which is used to implement the three-dimensional solidification crack sensitivity prediction system of the aluminum alloy laser welding weld.

[0082] The present invention is specifically implemented:

[0083] Example 1: Prediction of solidification crack sensitivity during three-dimensional solidification process of aluminum alloy laser welding under different nucleation rates

[0084] 1. First, a macroscopic numerical simulation is performed to obtain the cooling rate of the layout area when the weld is stable.

[0085] (1) Macroscopic heat and mass transfer schematic diagram and control equations are as follows Figure 3 The main welding process parameters are: laser welding power 10kW, welding speed 110mm / s; the calculation domain information is as follows Figure 4 As shown; the thermal physical parameters of aluminum alloy are: liquid metal density 2350kg m -3 , solid metal density 2670kg m -3 , viscosity 1.3×10 -3 kg m -1 s -1 、Liquid relative heat 1170J kg -1 K-1 、Solid specific heat 1040J kg -1 K -1 、Liquid phase thermal conductivity 90W m -1 K -1 、Solid phase thermal conductivity 150W m -1 K -1 , liquidus temperature 913.15K, solidus temperature 813.15K, heat transfer coefficient 20W m -2 K -1 Surface tension: 0.907N m -1 , latent heat of fusion 3.62×10 5 J kg -1 , latent heat of vaporization 1.08×10 7 J kg -1 , surface tension gradient -0.271×10 -3 N m -1 K -1 .

[0086] (2) Numerical simulation calculation to obtain the local cooling rate when stable. Figure 5 As shown, the cooling rate at this time is 1672K / s.

[0087] 2. Mushy zone microstructure simulation and Tf S Curve acquisition

[0088] (1) Schematic diagram of microscopic multi-element three-dimensional polycrystal phase field model and control equations are as follows Figure 6 Thermophysical parameters required for simulation: initial Cu concentration 4.0wt%, pure Al melting temperature 933.47K, liquidus slope in Al-Cu -5.08 ((Tm-Tl) / c0), Al-Cu distribution coefficient 0.169 ((Tl-Tm) / (Ts-Tm)), diffusion coefficient of Cu in liquid phase 3.0×10-9m 2 s -1 、The diffusion coefficient of Cu in the solid phase is 1.0×10-12m 2 s -1 、Al-Cu Gibbs-Thompson coefficient 2.4×10 -7 K m, anisotropy (ε4) 0.02.

[0089] (2) The three-dimensional microstructures under different nucleation rates are simulated. The simulation results are as follows: Figure 7 As shown in (a), under low nucleation rate conditions, as the temperature decreases, the initial solidification f SThe rate of increase slows down. This may be because the supercooling is small at this time and the grain growth is slow. In addition, due to the low equilibrium concentration of the liquid phase, the solute discharged from the solid phase can easily reach equilibrium near the solid-liquid interface, resulting in a slow growth rate. As the temperature further decreases, the supercooling increases, and the liquid phase equilibrium concentration limit increases. At this time, the smaller solid phase area needs to grow rapidly to reach equilibrium. In the late stage of solidification, the solid phase has occupied most of the area, and the distribution of liquid solute is basically balanced, causing the supercooling to become smaller again, which makes f S The change of f also slows down. For equiaxed crystals with high nucleation rate, S The change is relatively gentle, and the solidification process slows down significantly only in the later stage of solidification. Furthermore, the change of the solidification crack sensitivity coefficient of the three-dimensional microstructure with temperature was calculated, and the results are as follows: Figure 7 (b) The results show that during the temperature reduction process, the solidification crack sensitivity first fluctuates gently and then increases sharply. Compared with equiaxed crystals with high nucleation rate, the solidification crack sensitivity is larger at first, then smaller, and finally remains larger in the later stage of solidification.

[0090] Example 2: Comparison of solidification crack sensitivity between dendritic columnar crystals and non-dendritic columnar crystals

[0091] 1. First, microscopic numerical simulation is performed to obtain the microstructural morphology of the dendrite growth directional solidification stability under different primary dendrite spacings.

[0092] The microscopic simulation results are as follows Figure 8 As shown. It can be found that when the distance between primary dendrites is small, secondary dendrites are difficult to form, and the liquid phase channel is smooth and continuous. When the distance between primary dendrites is large, secondary dendrites will be generated, and some small tertiary dendrites may exist. During the solidification process, the disturbance of temperature and solute will lead to the formation of secondary dendrites. The interface instability and large supercooling caused by solute disturbance are the reasons for the formation of secondary dendrites.

[0093] 2. A portion of the microstructure of the mushy zone is cut out for simulation and comparative analysis of solidification crack sensitivity.

[0094] Fig. 9 The figure shows the change of the solid-liquid interface morphology of dendritic and non-dendritic columnar crystals with temperature. It can be observed from the figure that as the temperature decreases, both columnar crystals begin to coarsen. The fluctuation of the solid-liquid interface on the non-dendritic columnar crystal gradually becomes smooth. Subsequently, bridging occurs between the primary dendrites, and only some independent droplets remain. For the dendritic columnar crystals, they will also coarsen as the temperature decreases. Some small secondary dendrites will be melted. As the temperature decreases, the tips of the secondary dendrites begin to gradually approach each other and eventually achieve bridging. At this time, the liquid phase channel is not smooth, such as Fig. 9 shown.

[0095] The Kou model is selected as the basic criterion for predicting solidification crack sensitivity. This criterion is derived based on the growth of columnar crystals in three-dimensional space. Based on the physical basis, Kou et al. comprehensively considered the three factors of grain separation caused by external forces, the growth of adjacent grains, and the shrinkage of residual liquid along the grain boundaries, and derived a new SCS criterion. The specific expression is as follows:

[0096]

[0097] In the formula, ε local is the local stress, fS is the solid fraction, β is the solidification shrinkage, T is the temperature, v z is the flow rate of the intercrystalline liquid.

[0098] When the separation rate of adjacent grains is greater than the grain growth and the residual liquid phase along the grain boundary, solidification cracks will occur. After further simplification, when f S When it is close to 1, |dT / d(f S ) 1 / 2 The maximum value of | is the solidification crack sensitivity index of the weld.

[0099] Furthermore, Fig.10 The Tf of dendritic and non-dendritic columnar crystals was calculated. S The solidification crack sensitivity is calculated based on the Kou model. S =0.9645 (i.e. f B value), while the dendrite columnar crystal bridges f S =0.8711 (i.e. f B In addition, the crack sensitivity of dendritic columnar crystals is low, only 1 / 6 of that of cellular crystals. This shows that the smooth liquid phase channel of columnar crystals in the late solidification stage is not conducive to inhibiting solidification cracks. This is because different liquid phase channel morphologies have an impact on the late solidification stage f B The value has a huge impact, resulting in significant differences in the solidification crack sensitivity of different grain morphologies. When the microstructure morphology is non-dendritic columnar crystals, there is less residual liquid in the smooth liquid phase channel, and the reflux channel is single, which makes it impossible for the residual liquid to be effectively replenished in time when the solidification cracks caused by tensile stress initiate. This will inevitably increase the solidification crack sensitivity. When the microstructure morphology is dendritic columnar crystals, the secondary or even higher-order dendrites can be bridged in advance. The liquid phase between the dendrites is sufficient, and the residual liquid can replenish the dendrite fracture caused by tensile stress in time, thereby reducing the formation of solidification cracks.

[0100] Example 3: Prediction of solidification crack sensitivity considering grain boundary energy

[0101] 1. Relationship between grain boundary energy and orientation difference between grains

[0102] This method adopts the multiphase field model used by Guo et al., which can consider the effect of interface energy of adjacent grains under different orientation differences on microstructure growth. The interface energy relationship adopts the relationship between grain boundary energy and orientation difference proposed by Read-Shockley et al.:

[0103] σ SS =2.2σ SL [θ / θ m ][1-ln(θ / θ m )]

[0104] where θ is the orientation difference between two adjacent grains, σ SS is the intergranular energy, θm is the angle at which the grain interface energy reaches its maximum value, and σ SL is the solid-liquid interface energy. In the present invention, θm = 20°. If the orientation difference between adjacent grains is greater than this value, the grain boundary energy between grains remains unchanged, σ SS =2.2σ SL .

[0105] 2. Prediction of solidification crack sensitivity considering different grain orientation differences between adjacent grains and interface energy differences caused by different grain orientation differences

[0106] Two grains with different orientations are set in the calculation domain. Different from Example 2, in order to better compare the simulation results, the influence of noise in the solute is not considered in this example. Instead, secondary dendrites are directly generated by designing the initial secondary dendrites. The initial conditions are as follows: Figure 1 As shown in the figure, the initial solid phase is the yellow area, and the rest of the area is set as liquid phase. S The values ​​of are set differently, therefore, the solidification crack sensitivity between dendrites is only indirectly described qualitatively through the overlapping behavior. Fig.11 The simulation results of the solid-liquid interface of the columnar crystal region with temperature under different orientation differences are shown in the figure. It can be seen from the figure that when the orientation difference of adjacent grains is 0°, the secondary dendrites grow synchronously. When the dendrite arms begin to contact, the dendrites directly bridge ( Fig.11 a)). However, grain bridging becomes difficult due to the influence of grain misorientation and interfacial energy ( Fig.11 (b) and (c)). Fig.11 (b) AA' line and Fig.11 The BB' line in (c) represents the boundary between grains. The liquid fraction value at the eutectic temperature at each point on the line is as follows: Fig.12 As shown in the figure. The arrow indicates that the two adjacent grains have been bridged. Compared with the orientation difference of 10°, the dendrites have almost no bridges when the orientation difference is 20°. This shows that when the interface energy exists, even at the eutectic temperature, there is still a large amount of residual liquid between the two adjacent grains. And the liquid phase channel is relatively smooth, which inevitably increases the solidification crack sensitivity of the columnar crystal area.

[0107] Based on the above simulation results, there are two possible reasons for the solidification cracks in the columnar crystal region of single laser welding of aluminum alloy medium and thick plates: First, the columnar crystal region in the weld sometimes occupies more than half of the weld, and the columnar crystals in this area are mainly non-dendritic, without obvious secondary dendrites to facilitate the bridging of adjacent grains to reduce the sensitivity of solidification cracks. Secondly, due to competitive growth and other reasons, there may be a large orientation difference between adjacent grains, which may result in no overlap when the temperature drops to the eutectic temperature, which easily leads to the generation of solidification cracks.

[0108] 3. By adopting the above scheme, the present invention has the following advantages over the prior art: (1) The present invention accurately calculates the overlap point temperature / solid phase fraction (T / ) of adjacent dendrites in the polycrystalline structure of the weld mushy zone through macro-micro thermal-mass coupling simulation of laser welding. B / f B ) and Tf S curve; (2) A new method for predicting solidification crack sensitivity by integrating microstructural information was proposed, which achieved accurate prediction of solidification crack sensitivity in aluminum alloy laser welding and revealed the solidification crack inhibition mechanism of ultrafine equiaxed crystal structure, which shortened the intergranular liquid phase channel and reduced solute segregation. This has very important engineering application significance for achieving solidification crack-free welding of high-strength aluminum alloy thick-walled components.

[0109] During the welding process, welding parameters (such as laser power, welding speed and gas flow) will fluctuate with changes in the environment and material state, thus affecting the stability of the temperature field. The temperature field acquisition module monitors these parameters in real time through the dynamic feedback adjustment unit. The dynamic feedback adjustment unit obtains the current welding parameters through sensors, inputs them into the control system, and adjusts the relevant parameters in the flow and heat transfer control equations, ray tracing control equations, driving force control equations and thermal boundary control equations based on real-time data. In this way, the temperature field data can be dynamically adjusted according to the actual welding conditions, which improves the real-time and accuracy of the temperature field data and provides a reliable basis for the accurate simulation of the microstructure during the solidification process of the weld.

[0110] Optimization of 3D microstructure simulation accuracy of grain growth direction prediction unit

[0111] The grain growth direction prediction unit in the microstructure simulation module predicts the growth direction of grains based on the gradient distribution of the temperature field. Specifically, when the temperature field data is input into the grain growth direction prediction unit, the unit calculates the temperature gradient and uses the gradient information to predict the growth direction and speed of the grains in the three-dimensional mushy zone. Subsequently, combined with the grain boundary energy data under the overlapping conditions of adjacent grains, the grain growth direction prediction unit can simulate how grains interact with adjacent grains during the solidification process and generate a more accurate grain morphology evolution model. In this way, not only the simulation accuracy of the grain boundary temperature and solid phase fraction data is improved, but also the accuracy of the overall microstructure simulation is improved, thereby providing more refined microscopic data support for crack sensitivity prediction.

[0112] Crack sensitivity prediction and risk classification of data comparison and verification units

[0113] The data comparison and verification unit in the crack sensitivity prediction module quantifies the crack sensitivity of the weld by calculating the solidification crack sensitivity value SCS. First, the system calculates the SCS based on the T-fS curve, grain type (equiaxed crystal or columnar crystal) and the numerical value generated by the calculation dimension, and passes the result to the data comparison and verification unit. The unit compares the calculated SCS value with the preset crack sensitivity threshold and classifies the crack risk of the weld according to the size of the SCS value. Specifically, the higher the SCS value, the greater the sensitivity of solidification cracks; the data comparison and verification unit divides the risk into different levels such as low, medium and high according to different SCS intervals. Finally, the system generates a visual report of crack sensitivity, displays the crack sensitivity and crack risk level in the form of a chart, and gives corresponding adjustment suggestions. This makes the optimization of welding process parameters intuitive and efficient, helping operators to adjust welding parameters in time and reduce crack risks.

[0114] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0115] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A system for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds, characterized in that: The system includes: Temperature field acquisition module, which is used to establish a macroscopic heat and mass transfer model for laser welding based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations, and to extract the temperature field data of the entire weld at different times during the welding process; The microstructure simulation module is used to input the temperature field data into the isothermal three-dimensional mushy zone microstructure simulation, simulate and obtain the grain boundary energy, temperature and solid phase fraction data under the overlapping conditions of adjacent grains; Data processing and visualization module, used to process the numerical results of microstructure simulation and generate temperature-solid fraction curves and liquid fraction at adjacent grain boundaries; The crack sensitivity prediction module is used to draw the corresponding curve based on the T-fS curve and the grain type (equiaxed crystal or columnar crystal) and calculation dimension in the calculation area, and calculate the solidification crack sensitivity value SCS.

2. The system according to claim 1, characterized in that The temperature field acquisition module further includes a dynamic feedback adjustment unit, which is used to dynamically adjust the parameters of the flow and heat transfer control equation, the ray tracing control equation, the driving force control equation and the thermal boundary control equation according to the welding parameters (such as laser power, welding speed and gas flow) monitored in real time during the welding process, so as to improve the real-time and accuracy of the temperature field data; The microstructure simulation module also includes a grain growth direction prediction unit, which is used to predict the growth direction of grains based on the gradient distribution of the temperature field, and to simulate the morphological evolution of grains in the three-dimensional mushy zone in combination with the grain boundary energy data under the overlapping conditions of adjacent grains, so as to further improve the simulation accuracy of grain boundary temperature and solid phase fraction data.

3. The system according to claim 1, characterized in that The crack sensitivity prediction module includes a data comparison and verification unit, which is used to compare the predicted solidification crack sensitivity value SCS with a preset crack sensitivity threshold, and to grade the crack risk according to different SCS intervals, and to output a visual report of the crack sensitivity to facilitate the optimization and adjustment of welding process parameters.

4. The system for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds according to claim 1, characterized in that: The temperature field acquisition module also includes a three-dimensional geometric modeling unit, which is used to generate a three-dimensional model based on the actual welding sample, perform meshing, set thermophysical parameters, initial conditions and boundary conditions, and perform macroscopic heat flow calculation under thermal-mass-force coupling.

5. The system for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds according to claim 1, characterized in that: The microstructure simulation module includes a grain overlap judgment unit, which is used to judge whether the grains overlap according to whether the liquid phase fraction at the boundary of two adjacent grains in the simulation is less than 0.5, and extract the temperature and solid phase fraction of the overlap point based on this information.

6. A method for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding weld, characterized in that: The following steps are involved: Step 1, obtaining macroscopic temperature field information; A macroscopic heat and mass transfer model of laser welding is established based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations. Step 2: Microstructure simulation of the mushy area and acquisition of key information; The temperature field data obtained from the macroscopic simulation is used as input to perform isothermal three-dimensional mushy zone microstructure simulation considering the grain boundaries of adjacent grains. Step 3, solidification crack sensitivity prediction; Based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension.

7. The method for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding weld according to claim 6, characterized in that: The macroscopic temperature field information is obtained: A macroscopic heat and mass transfer model of laser welding is established based on the flow and heat transfer control equations, ray tracing control equations, driving force control equations, and thermal boundary control equations. Three-dimensional geometric modeling is carried out based on the actual welding specimen, the model is meshed, and the thermophysical property parameters, initial conditions, and boundary condition information are set to calculate the macroscopic heat flow of aluminum alloy laser welding under thermal-mass-force coupling. The depth of penetration and width of the simulation results are observed, and the temperature field data of the entire weld at different times are extracted when the depth of penetration and width of the weld are basically stable.

8. The method for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds according to claim 6, characterized in that: The mushy zone microstructure simulation and key information acquisition: The temperature field data obtained from the macroscopic simulation is used as input, and the grain boundaries of adjacent grains can be considered to perform isothermal three-dimensional mushy zone microstructure simulation; the numerical simulation results are visualized, and when two adjacent grains overlap, the judgment condition is that the liquid phase fraction at the adjacent grain boundary is less than 0.

5. At this time, the temperature of the entire calculation domain is used as the overlap point temperature TB, and the solid phase fraction of the calculation domain is used as the overlap point solid phase fraction fB; the temperature-solid phase fraction curve T-fS curve in the entire calculation domain is extracted; The calculation dimension includes two-dimensional / three-dimensional; The solidification crack susceptibility prediction: Based on the T-fS curve, the crack sensitivity value SCS is calculated according to whether the calculation area is equiaxed crystal or columnar crystal and the calculation dimension: (1) For a two-dimensional columnar crystal, draw a T-|dT / d(fs)| curve. When f=fB, SCS=|dT / d(fs)|; (2) For a two-dimensional equiaxed crystal, draw the T-|dT / d(fs)1 / 2| curve. When f=fB, SCS=|dT / d(fs)1 / 2|; (3) For three-dimensional columnar crystals, draw the T-|dT / d(fs)1 / 2| curve. When f=fB, SCS=|dT / d(fs)1 / 2|; (4) For three-dimensional equiaxed crystals, draw the T-|dT / d(fs)1 / 3| curve. When f=fB, SCS=|dT / d(fs)1 / 3|.

9. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the method for predicting three-dimensional solidification crack sensitivity of aluminum alloy laser welding welds as claimed in any one of claims 6 to 8.

10. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the three-dimensional solidification crack sensitivity prediction system for aluminum alloy laser welding welds as described in any one of claims 1 to 5.

Images